Why would giving my AI more data make it perform worse?
Why would giving my AI more data make it perform worse?


A lot of possible reasons:


In forecasting, you could have a seasonality. If you have it exactly 3 times, then it is good. If you have it 3.5 times, it becomes worse because it overfits on the months which occur more often than the others.
Data quality: In practice, improving the quality of data often yields better results (see Analysis and Optimization of Convolutional Neural Network Architectures, page 15 (Analysis Techniques) for 7 approaches to improve your results)
Instable training / bad luck: some architectures / problems are super instable. You can execute the randomly initialized training 5 times and get vastly different results.